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FastDeploy/examples/vision/detection/paddledetection/python/infer_mask_rcnn.py
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2022-11-28 22:01:51 +08:00

78 lines
2.1 KiB
Python

import fastdeploy as fd
import cv2
import os
def parse_arguments():
import argparse
import ast
parser = argparse.ArgumentParser()
parser.add_argument(
"--model_dir",
default=None,
help="Path of PaddleDetection model directory")
parser.add_argument(
"--image", default=None, help="Path of test image file.")
parser.add_argument(
"--device",
type=str,
default='cpu',
help="Type of inference device, support 'cpu' or 'gpu'.")
parser.add_argument(
"--use_trt",
type=ast.literal_eval,
default=False,
help="Wether to use tensorrt.")
return parser.parse_args()
def build_option(args):
option = fd.RuntimeOption()
if args.device.lower() == "gpu":
# option.use_gpu()
print(
"""GPU inference with Backend::Paddle in python has not been supported yet. \
\nWill ignore this option.""")
if args.use_trt:
# TODO(qiuyanjun): may remove TRT option
# Backend::TRT has not been supported yet.
print(
"""Backend::TRT has not been supported yet, will ignore this option.\
\nPaddleDetection/MaskRCNN has only support Backend::Paddle now."""
)
return option
args = parse_arguments()
if args.model_dir is None:
model_dir = fd.download_model(name='mask_rcnn_r50_1x_coco')
else:
model_dir = args.model_dir
model_file = os.path.join(model_dir, "model.pdmodel")
params_file = os.path.join(model_dir, "model.pdiparams")
config_file = os.path.join(model_dir, "infer_cfg.yml")
# 配置runtime,加载模型
runtime_option = build_option(args)
model = fd.vision.detection.MaskRCNN(
model_file, params_file, config_file, runtime_option=runtime_option)
# 预测图片检测结果
if args.image is None:
image = fd.utils.get_detection_test_image()
else:
image = args.image
im = cv2.imread(image)
result = model.predict(im)
print(result)
# 预测结果可视化
vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("visualized_result.jpg", vis_im)
print("Visualized result save in ./visualized_result.jpg")